Nonlinear Correction of Sensor Calibration

To satisfy the need of correcting the nonlinear characteristic of the sensor between the input and output,this paper uses the least squares,polynomial curve fitting and the neural network fitting methods to do the nonlinear correction,and compares the linearities after fitting.The results show that all the three curve fitting methods can realize the nonlinear correction for the data of sensor calibration,but the linearity after neural network fitting is smaller than that of the other fitting methods.The method of neural network fitting is simple and practical,and it can be used for the calibration data processing of all types of nonlinear system and has significant impact on application areas.